Three Ways Agentic AI Will Redefine Sustainable Supply Chains

Agentic AI is quickly moving from concept to cornerstone in supply chain technology innovation. At its aim10x event in Dallas, for example, o9 Solutions unveiled strategic investments in AI-powered capabilities like generative root cause analysis. Similarly, at Kinaxis’s Amsterdam event, agentic AI was in the spotlight as the future of demand forecasting and supply chain agility.

However, despite software vendors’ vast investment in agentic AI, only 17% of firms currently use multiple AI agents for sustainability and ESG initiatives. Verdantix anticipates that adoption will expand across functions as the agentic era matures and organizations complete the necessary architectural and data transformations. Meanwhile, as agentic AI continues to evolve, its role in shaping sustainable supply chains will only grow more critical, becoming a foundational tool for driving sustainability and business resilience across the supply chain. Drilling down into this trend, Verdantix has identified three ways agentic AI will transform supply chain sustainability:

• Accelerating adaptability to supply chain disruptions.

  Multi-agent AI systems continuously monitor operations and transactions, detecting anomalies and threshold breaches that may signal supply chain disruptions. Beyond real-time insights, AI agents enrich scenario analysis by uncovering hidden correlations, challenging the conventional trade-off between sustainability and business resilience. For example, an AI agent analysing live weather data could collaborate with another agent managing transportation logistics to reroute shipments ahead of extreme weather events, preventing delays, lowering fuel consumption and reducing environmental impact.

• Streamlining data integration for sustainable procurement.

  AI agents can collaborate across organizational siloes to integrate, analyse and escalate actions, conducting routine and underfunded tasks. For example, an AI agent can support sustainable procurement by collecting data on multiple suppliers and assessing them on a defined sustainability criterion, supporting procurement teams as they align supplier and sustainability requirements while balancing risk and operational needs.

• Empowering teams to embed sustainability into core operations.Agentic AI can learn independently from new data and make informed decisions with minimal human oversight. This allows supply chain managers to shift their focus from routine monitoring to identifying exceptions and ensuring smooth operations. For instance, supply chain planners can use agentic AI to gain real-time visibility into sustainability KPIs, allowing the AI agent to adjust processes autonomously. This frees teams to focus on business innovation and transformational processes, and ensures sustainability is included as a core component of supply chain strategies.

To learn more about how AI can transform sustainability strategies, see AI Applied Radar: AI Applied To Sustainability Management. For deeper insights into corporate investment priorities and technology preferences for AI solutions, see Verdantix Global Corporate Survey 2025: AI Budgets, Priorities And Tech Preferences.